Data Scientist

Level

Senior

Department

Type

Full Time

Project

NDA

Locations:

Ukraine

Job Details

Posted on:

July 3, 2026

Job ID:

C8zah2

About the Company

Established in 2004, ALLSTARSIT was founded with a clear vision: to enhance the landscape of global IT employment by bridging the gap between companies and skilled professionals. The core belief was that assembling a team shouldn't be hindered by geographical constraints. Fast forward to the present day, ALLSTARSIT stands as an international outstaffing service provider committed to change the way businesses recruit, compensate, and oversee top talent worldwide.

With operational hubs scattered across Europe, Asia, and LATAM, and its headquarters situated in San Francisco, US, the company boasts a workforce of over 1,000 adept professionals. Spanning across more than 20 countries, ALLSTARSIT offers a diverse range of skilled employees across various verticals, including AI, cybersecurity, healthcare, fintech, telecom, media, and so on.

About the Project

Specialization

Headquarters

Years on the market

Team size and structure

Current technology stack

Required skills:

M.Sc. in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative discipline
At least 3 years of hands-on Data Science experience, delivering end-to-end solutions into production environments
Deep understanding of machine learning theory and practical model behavior
Expertise in Python and the modern Data Science ecosystem (NumPy, Pandas, Scikit-learn, PyTorch / TensorFlow, etc.)
Solid understanding of LLM architectures and fine-tuning methodologies
Excellent interpersonal skills and proven ability to work within multidisciplinary product teams
Strong analytical rigor and structured problem-solving capability

Scope of work:

Develop Data Science initiatives from problem definition through validation, production deployment, and monitoring of AI systems
Develop security-focused AI agents and reasoning systems
Develop advanced ML capabilities, including predictive modeling, anomaly detection, and classification
Adapt and fine-tune LLM technologies for domain-specific security use cases